
Answer to RQ1: In line with the previous study of Abdollahpouri et al. [1]}, our experiments demonstrate that different users have a considerably different tendency towards popular items. Moreover, we discovered that around 83% of users have read at least 20% of unpopular books in their profile and expect to receive some of these items in recommendations. Our result further reveals that users with larger profile sizes who contribute most to the system have diverse tastes and interact with a substantial amount of unpopular items.

Answer to RQ2: Our results for various state-of-the-art recommendation algorithms demonstrate that most algorithms are unfair to users who have a niche or diverse taste in books in terms of popularity, i.e., these users receive recommendations that have lower accuracy and mainly consist of popular books. In addition, the study shows popularity bias negatively affects all user groups, even those focusing on bestsellers, but the magnitude of this effect varies greatly depending on the user group.

